class_docstr: Abstract Layer for tensorflow_text tokenizers.
  
  Input shape:
    N-D (2D as default) tensor with shape: `(batch_size, input_length)`.
  
  Output shape:
    (N+1)-D (3D as default) tensor with shape:
      `(batch_size, input_length, token_dim)`.
docstr: Compute the output tensor signature of the layer based on the inputs.
  
  Args:
    input_signature: Single TensorSpec or nested structure of TensorSpec
      objects, describing a candidate input for the layer.
  
  Returns:
    Single TensorSpec or nested structure of TensorSpec objects, describing
      how the layer would transform the provided input.
  
  Raises:
    TypeError: If input_signature contains a non-TensorSpec object.
docstr_tok: ["Compute","the","output","tensor","signature","of","the","layer","based","on","the","inputs",".","Args",":","input_signature",":","Single","TensorSpec","or","nested","structure","of","TensorSpec","objects",",","describing","a","candidate","input","for","the","layer",".","Returns",":","Single","TensorSpec","or","nested","structure","of","TensorSpec","objects",",","describing","how","the","layer","would","transform","the","provided","input",".","Raises",":","TypeError",":","If","input_signature","contains","a","non-TensorSpec","object","."]
code: def compute_output_signature(self, input_signature):
      """Compute the output tensor signature of the layer based on the inputs.
  
      Args:
        input_signature: Single TensorSpec or nested structure of TensorSpec
          objects, describing a candidate input for the layer.
  
      Returns:
        Single TensorSpec or nested structure of TensorSpec objects, describing
          how the layer would transform the provided input.
  
      Raises:
        TypeError: If input_signature contains a non-TensorSpec object.
      """
  
      def CheckAndReturnShape(s):
          if not isinstance(s, tf.TensorSpec):
              raise TypeError(
                  "Only TensorSpec signature types are supported, "
                  "but saw signature signature entry: {}.".format(s)
              )
          return s.shape
  
      input_shape = CheckAndReturnShape(input_signature)
      output_shape = self.compute_output_shape(input_shape)
      return tf.TensorSpec(dtype=tf.string, shape=output_shape)
  
imports: import os
  import tensorflow
  from tensorflow.python.ops import lookup_ops
  from tensorflow.python.ops.ragged import ragged_conversion_ops
  from tensorflow_text.python.ops import unicode_script_tokenizer
  from tensorflow_text.python.ops import whitespace_tokenizer
  from tensorflow_text.python.ops import wordpiece_tokenizer
label_desc: Use image node_id 6 for calling the TokenizerBase obj's underlying member method code with example usage: obj.compute_output_signature(input_signature) and returns: tf, s